Visceral adipose tissue but not subcutaneous adipose tissue is associated with urine and serum metabolites

PLoS One. 2017 Apr 12;12(4):e0175133. doi: 10.1371/journal.pone.0175133. eCollection 2017.

Abstract

Obesity is a complex multifactorial phenotype that influences several metabolic pathways. Yet, few studies have examined the relations of different body fat compartments to urinary and serum metabolites. Anthropometric phenotypes (visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), the ratio between VAT and SAT (VSR), body mass index (BMI), waist circumference (WC)) and urinary and serum metabolite concentrations measured by nuclear magnetic resonance spectroscopy were measured in a population-based sample of 228 healthy adults. Multivariable linear and logistic regression models, corrected for multiple testing using the false discovery rate, were used to associate anthropometric phenotypes with metabolites. We adjusted for potential confounding variables: age, sex, smoking, physical activity, menopausal status, estimated glomerular filtration rate (eGFR), urinary glucose, and fasting status. In a fully adjusted logistic regression model dichotomized for the absence or presence of quantifiable metabolite amounts, VAT, BMI and WC were inversely related to urinary choline (ß = -0.18, p = 2.73*10-3), glycolic acid (ß = -0.20, 0.02), and guanidinoacetic acid (ß = -0.12, p = 0.04), and positively related to ethanolamine (ß = 0.18, p = 0.02) and dimethylamine (ß = 0.32, p = 0.02). BMI and WC were additionally inversely related to urinary glutamine and lactic acid. Moreover, WC was inversely associated with the detection of serine. VAT, but none of the other anthropometric parameters, was related to serum essential amino acids, such as valine, isoleucine, and phenylalanine among men. Compared to other adiposity measures, VAT demonstrated the strongest and most significant relations to urinary and serum metabolites. The distinct relations of VAT, SAT, VSR, BMI, and WC to metabolites emphasize the importance of accurately differentiating between body fat compartments when evaluating the potential role of metabolic regulation in the development of obesity-related diseases, such as insulin resistance, type 2 diabetes, and cardiovascular disease.

MeSH terms

  • Adult
  • Biomarkers / blood
  • Biomarkers / urine
  • Female
  • Humans
  • Intra-Abdominal Fat / metabolism*
  • Male
  • Metabolome
  • Middle Aged
  • Obesity / blood*
  • Obesity / urine*
  • Subcutaneous Fat / metabolism*

Substances

  • Biomarkers

Grants and funding

This study was conducted within the framework of the pilot studies of the German National Cohort (www.nationale-kohorte.de), grant number 01ER1001A-I. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.